Lasso Regression is a Machine Learning technique designed to enhance the accuracy and interpretability of statistical models. It imposes an L1 penalty, shrinking less important coefficients to zero, thereby performing Feature Selection and yielding simpler, more robust models. This method elegantly balances model fit with parsimony.