Inconel 718, a nickel-based superalloy, due to its divergent solitary features, has a variety of applications. However, due to its intrinsic qualities such as high strength, hardness, poorer heat conductivity, and work hardening propensity, the cutting of this alloy is difficult. The most appropriate nanofluid was found using the technique for order preference by similarity to ideal solution (TOPSIS) analysis. Aluminum oxide and multi-wall carbon nanotubes, blended with palm oil, are found to be better options for machining. The study utilized a hybrid nanofluid to examine the shear angle and chip thickness ratio in turning Inconel 718 under minimal quantity lubrication (NFMQL). The chip thickness ratio and shear angle increased with cutting speed and decreased with an increase in feed and depth of cut. The chip thickness ratio and shear angle were predominantly affected by the depth of cut, followed by cutting speed and feed. The correlation coefficient found for the developed mathematical models is close to 0.9, showing that the developed models could be valid in forecasting the chip thickness ratio and shear angle within the parameters’ chosen domain. The chip morphology study revealed that loosely coiled chips were produced, which enabled quick heat removal. SEM images showed clean breaking of chip edges with minimal microparticle deposition on the chip surface, owing to the excellent cooling and lubricating properties of the hybrid nanofluids.