This paper presents a winner-take-all (WTA) approach for implementing background inhibition in neuromorphic Ion-Sensitive Field-Effect Transistor (ISFET) arrays. The integration of WTA, integrate and fire (I\&F) and CMOS-based electrochemical readout paves the way for the next generation of Lab-on-chip (LoC) platforms to diagnose and classify infectious diseases using sensor learning. The integration of the WTA in individual pixels allows for spatial adaptive filtering which can help eliminate the dynamic background due to ion accumulation at the gate of the sensors. The readout is done through address-event representation (AER) to enable ultra-low power data acquisition. The cluster implementation makes the design scalable for implementation as part of a large-scale integrated sensor. The paper proposes a novel ultra-low powered approach where the pixel power consumption in the array ranges from 171.6nW to 410.9nW with an expected sensitivity of 20.2KHz/dpH to 29.1KHz/dpH. The sensor array is implemented in TSMC 0.18um.