Explainable Artificial Intelligence aims to assist in opening the blackbox of opaque algorithms, especially present in machine learning systems,so they can earn due trustworthiness. This work employs a systematic literature review in order to understand how the concepts of explainability andinterpretability, among others, are defined in this context. It offers a structured vocabulary to better comprehend and classify artificial intelligence systems and models, as well as the techniques used to make them more intelligible. Inspired by Human-Centered Computing notions, it becomes crucial to consider the audience to which explanations are owed, emphasizing that it is composed of a community of heterogeneous users.