Central moments are statistical measures that provide insights into the shape and variability of a probability distribution, calculated as the expected value of a specified power of deviations from the mean. They are crucial for understanding the distribution's characteristics, such as skewness and kurtosis, which describe asymmetry and tail heaviness, respectively.