Contrastive Loss is a loss function used primarily in machine learning for tasks that involve learning similarity or dissimilarity between pairs of inputs. It works by minimizing the distance between similar pairs and maximizing the distance between dissimilar pairs in the embedding space, effectively teaching the model to distinguish between different classes or categories.