Quantum machine learning explores how quantum computers, which exploit physics phenomena like superposition and entanglement, could speed up or improve machine learning tasks such as optimization and pattern recognition. The field is still experimental: today's quantum hardware is small and noisy, so practical business advantages remain rare. Think of it as research into a future engine, not a tool for tomorrow's project. Banks and logistics firms follow it for long-term problems like portfolio optimization and route planning across African trade networks.