A User-Item Matrix is a foundational data structure in recommendation systems, where rows represent users and columns represent items, with entries indicating user preferences or interactions with items. It is primarily used to analyze and predict user behavior by leveraging collaborative filtering techniques to recommend items to users based on patterns of user-item interactions.