Negative binomial regression is a type of regression analysis used for count data where the variance exceeds the mean, addressing overdispersion by introducing an extra parameter. It is particularly useful when the data exhibits a high degree of variability that cannot be captured by a Poisson distribution, making it ideal for modeling overdispersed count data in fields like epidemiology and ecology.