In machine learning and statistics, feature selection, also known as variable selection, attribute selection or variable subset selection, is the process of selecting a subset of relevant features (variables, predictors) for use in model construction.
Feature selection techniques are used for three reasons:
Simplification of models to make them easier to interpret by researchers/users
From https://en.wikipedia.org/wiki/Feature_selection