Local identifiability refers to the ability to uniquely estimate model parameters based on the observed data. For a parameter to be locally identifiable, small changes in its value should lead to detectable differences in the probability distribution of the observed data. This concept is crucial in ensuring that the parameters of a model can be accurately estimated from the data.