A Bayesian Network is a graphical model that represents a set of variables and their conditional dependencies using directed acyclic graphs. Each node in the graph represents a variable, while the edges (arrows) indicate the relationships between them. This structure allows us to visualize how different factors influence one another, making it easier to understand complex systems. By applying Bayes' theorem, a Bayesian Network can update the probability of a hypothesis as more evidence becomes available. This makes it a powerful tool for decision-making in various fields, such as medicine, finance, and artificial intelligence, where uncertainty is a key factor.