Linear discriminant analysis is a statistical method primarily employed for dimensionality reduction and supervised classification. It identifies linear combinations of variables that maximize the separation between multiple classes while minimizing variance within each class, thereby providing a projection suitable for distinguishing group memberships and building predictive models.