A linear classifier is a type of supervised learning algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector. It is particularly effective for binary classification tasks where the data is linearly separable, meaning that a straight line (or hyperplane in higher dimensions) can separate the classes.