diff --git a/sklearn/linear_model/_coordinate_descent.py b/sklearn/linear_model/_coordinate_descent.py
index b98cf08925910..0d196ee2d23eb 100644
--- a/sklearn/linear_model/_coordinate_descent.py
+++ b/sklearn/linear_model/_coordinate_descent.py
@@ -1276,9 +1276,7 @@ class Lasso(ElasticNet):
     reduces the variance of the estimates. Larger values specify stronger
     regularization. Alpha corresponds to `1 / (2C)` in other linear
     models such as :class:`~sklearn.linear_model.LogisticRegression` or
-    :class:`~sklearn.svm.LinearSVC`. If an array is passed, penalties are
-    assumed to be specific to the targets. Hence they must correspond in
-    number.
+    :class:`~sklearn.svm.LinearSVC`.
 
     The precise stopping criteria based on `tol` are the following: First, check that
     that maximum coordinate update, i.e. :math:`\\max_j |w_j^{new} - w_j^{old}|`