The log-likelihood function is a transformation of the likelihood function that simplifies the process of finding maximum likelihood estimates by converting products into sums, which are easier to differentiate. It is widely used in statistical modeling and machine learning for parameter estimation and hypothesis testing due to its mathematical convenience and numerical stability.