Continuous distribution refers to a type of probability distribution that describes the likelihood of a continuous random variable taking on a range of values. Unlike discrete distributions, which deal with distinct and separate values, continuous distributions allow for an infinite number of possible outcomes within a given interval. The probability of a continuous random variable assuming a specific value is always zero; instead, probabilities are determined over intervals. Common examples include the normal distribution, uniform distribution, and exponential distribution, which are widely used in statistics, machine learning, and various scientific fields to model real-world phenomena.