Likelihood is a concept that underlies most statistical modeling that falls under the heading of generalized linear model or GLMs.
When we fit any kind of statistical model to a dataset, the goal is to find solutions that either maximize the likelihood of the data, given the model (under a frequentist, maximum likelihood estimation framework), or maximize the likelihood of the data given the data and some prior information on the value of the parameters (under a more Bayesian framework).