Explore the role of principal components in machine learning algorithms, such as principal component analysis (PCA) and linear discriminant analysis (LDA). How do these dimensionality reduction techniques extract the most informative features or principal components from high-dimensional data sets to improve classification, clustering, and prediction accuracy in pattern recognition tasks ?