Non-Gaussian processes are stochastic processes that do not follow a normal distribution, often characterized by skewness, kurtosis, or heavy tails. They are crucial in fields like finance, telecommunications, and climate science, where data exhibits behavior that deviates from Gaussian assumptions, requiring specialized models and analysis techniques.