Visible Light Communication (VLC) is an emerging technology that uses light sources such as light-emitting diodes (LEDs) and lasers for data transmission. This is enabled by the IEEE 802.15.7 protocol, which supports deterministic communication through its guaranteed timeslot mechanism. VLC networks provide several advantages in terms of high bandwidth, security, and immunity to electromagnetic interference. Most of the works in VLC are centred around point-to-point communication and do not necessarily provide emphasis on the challenges due to blockage, deafness, or hidden node problems. In this work, we present a machine learning (ML)-optimized routing protocol (Q Light) that improves network throughput and reliability through the selection of efficient routes for the IEEE 802.15.7 protocol.