diff --git a/doc/source/whatsnew/v1.1.3.rst b/doc/source/whatsnew/v1.1.3.rst
index c1effad34ab93..bef38a2900901 100644
--- a/doc/source/whatsnew/v1.1.3.rst
+++ b/doc/source/whatsnew/v1.1.3.rst
@@ -37,6 +37,7 @@ Fixed regressions
 - Fixed regression in :class:`DataFrame` and :class:`Series` comparisons between numeric arrays and strings (:issue:`35700`, :issue:`36377`)
 - Fixed regression when setting empty :class:`DataFrame` column to a :class:`Series` in preserving name of index in frame (:issue:`36527`)
 - Fixed regression in :class:`Period` incorrect value for ordinal over the maximum timestamp (:issue:`36430`)
+- Fixed regression when adding a :meth:`timedelta_range` to a :class:``Timestamp`` raised an ``ValueError`` (:issue:`35897`)
 
 .. ---------------------------------------------------------------------------
 
diff --git a/pandas/core/arrays/timedeltas.py b/pandas/core/arrays/timedeltas.py
index 3eaf428bc64b2..4526fb9c8623c 100644
--- a/pandas/core/arrays/timedeltas.py
+++ b/pandas/core/arrays/timedeltas.py
@@ -450,7 +450,7 @@ def _add_datetimelike_scalar(self, other):
         result = checked_add_with_arr(i8, other.value, arr_mask=self._isnan)
         result = self._maybe_mask_results(result)
         dtype = DatetimeTZDtype(tz=other.tz) if other.tz else DT64NS_DTYPE
-        return DatetimeArray(result, dtype=dtype, freq=self.freq)
+        return DatetimeArray._simple_new(result, dtype=dtype, freq=self.freq)
 
     def _addsub_object_array(self, other, op):
         # Add or subtract Array-like of objects
diff --git a/pandas/tests/arithmetic/test_timedelta64.py b/pandas/tests/arithmetic/test_timedelta64.py
index 64d3d5b6d684d..dd9b6269ce5bf 100644
--- a/pandas/tests/arithmetic/test_timedelta64.py
+++ b/pandas/tests/arithmetic/test_timedelta64.py
@@ -2136,3 +2136,20 @@ def test_td64arr_pow_invalid(self, scalar_td, box_with_array):
 
         with pytest.raises(TypeError, match=pattern):
             td1 ** scalar_td
+
+
+def test_add_timestamp_to_timedelta():
+    # GH: 35897
+    timestamp = pd.Timestamp.now()
+    result = timestamp + pd.timedelta_range("0s", "1s", periods=31)
+    expected = pd.DatetimeIndex(
+        [
+            timestamp
+            + (
+                pd.to_timedelta("0.033333333s") * i
+                + pd.to_timedelta("0.000000001s") * divmod(i, 3)[0]
+            )
+            for i in range(31)
+        ]
+    )
+    tm.assert_index_equal(result, expected)