The paper describes the exceptional importance of Explainable Artificial Intelligence (XAI) in the field of oncology informatics and its ability to increase the level of transparency and trust in the process of cancer diagnostics and treatment choices. XAI helps enhance patient outcomes and clinician confidence as interpretable AI models are incorporated with the clinical workflow to ensure a better understanding of challenging machine learning outputs. The paper identifies existing approaches, clinical implementation obstacles, and future opportunities to incorporate explainability into AI-based oncology systems to aid precision medicine and ethical health care provision