Univariate feature selection works by selecting features based on a univariate test statistic. Although it can seen as a preprocessing step to an estimator, scikit.learn exposes an object to wrap as existing estimator with feature selection and expose a new estimator:
This object takes another estimator, a scoring function that returns univariate p values, and a selection function that selects attributes.
Warning
A common case of non-functionning for feature selection is to use a regression scoring function with a classification problem.