Multiclass classification is a type of machine learning task where the goal is to assign an input data point to one of multiple possible categories or classes. In contrast to binary classification, where there are only two possible classes, multiclass classification involves predicting from three or more classes. This task can be challenging due to the increased number of classes and the potential for overlap between them. Various techniques and algorithms, such as logistic regression, support vector machines, decision trees, and neural networks, can be used to perform multiclass classification and accurately label data points into their respective categories.