Profile likelihood is a technique used in statistical inference to address the uncertainty of parameter estimates by focusing on a single parameter of interest while treating other parameters as nuisance parameters. It provides a way to construct confidence intervals and hypothesis tests that are robust to the presence of these nuisance parameters, often leading to more reliable inference in complex models.