1. A machine learning apparatus for learning (i) a power failure detection level, which is a value of a power supply voltage defined as a criterion for determination as to whether power failure has occurred on an AC power supply side of a motor control apparatus, and (ii) a power failure detection time, which is a time for which the power supply voltage on the AC power supply side of the motor control apparatus has been lower than the power failure detection level, in the motor control apparatus which converts AC power supplied from the AC power supply side into DC power, outputs the DC power to a DC link, further converts the DC power into AC power for driving a motor, and supplies the AC power to the motor, the machine learning apparatus comprising: a DC voltage measuring unit which measures a DC link voltage across two terminals of a DC link capacitor in the DC link; an AC voltage measuring unit which measures a value of the power supply voltage on the AC power supply side; an energy amount computation unit which computes an amount of energy stored in the DC link capacitor; a state observation unit which observes a state variable including data associated with the measured value of the power supply voltage on the AC power supply side, data associated with the computed amount of energy stored in the DC link capacitor, data indicating whether a protective operation for the motor control apparatus is successful, and data associated with motor output; and a learning unit which learns the power failure detection level and the power failure detection time, by repeating update of a function for changing the power failure detection level and the power failure detection time, based on the state variable.