Support Vector Machines (SVM) is a supervised machine learning algorithm used for classification and regression analysis. It aims to find the best boundary between classes by maximizing the margin between them. SVM is particularly useful in high-dimensional data and can handle non-linear data using a technique called the kernel trick.