Elastic Net is a regularization technique that linearly combines the penalties of L1 (Lasso) and L2 (Ridge) regularization to enhance model accuracy and interpretability, especially when dealing with highly correlated features. It is particularly useful in scenarios where the number of predictors exceeds the number of observations or when there are groups of correlated variables.