Feature selection is the process of choosing precise features, from a features pool. This helps in simplification, regularization and shortening training time. This can be done with various techniques: e.g. Linear Regression, Decision Trees.
The main difference between them is Feature selection keeps a subset of the original features while feature extraction creates new ones.