Visual question answering is a research field at the intersection of computer vision and natural language processing, focused on developing artificial intelligence systems that can answer natural language questions about the content of images. This domain investigates the complex challenge of integrating visual understanding from an image with linguistic comprehension of a question, requiring models to reason about the spatial, object, and semantic information depicted to generate a relevant and accurate textual response. Its significance lies in serving as a key benchmark for evaluating multimodal AI capabilities and enabling applications requiring human-like image understanding and interaction.