Lasso Regression is a linear model that addresses some problems of Ordinary Least Squares by imposing a penalty (or regularization term) to the weights

Lasso regression uses a L1 regularization.

This algorithm only selects some of the input features and completely discards others (depending on the value of the regularization term). It thus generally creates simpler output formulas than other linear models.