Hinge loss is a loss function primarily used for 'maximum-margin' classification, most notably with support vector machines, where it helps to create a decision boundary that maximizes the margin between different classes. It is particularly effective for binary classification tasks, as it penalizes misclassified points and those within the margin, encouraging a robust separation of classes.