A knowledge graph is a collection of linked concepts. It uses a graph structure to store semantically linked entities (e.g. objects, concepts, events).
Knowledge graphs help contextualize data - instead of treading a datum as a single, isolated fact, they store information on its relationship to other pieces of data. For instance, in a knowledge graph containing information on cars, each car could have a connection to its manufacturer; it's then easy for AI Applications to infer which cars are related.
Knowledge graphs have driven advances in applied machine learning. For instance Google uses a large, rich knowledge graph to inform and improve its search results - the snippets of information from searches are sourced from their knowledge graph.
Knowledge graphs tend to use graph databases to efficiently execute queries and searches.