Stable distributions are a class of probability distributions that generalize the normal distribution and are characterized by their heavy tails and skewness, allowing them to model data with infinite variance. They are defined by four parameters: location, scale, shape, and skewness, and are often used in finance and physics to model real-world processes with large fluctuations or outliers.