What does unconditional probability mean?

Hint: Here in this question we have to define the unconditional probability. Since it is the form of probability, firstly we know the definition and formula of the probability. Then we know about the unconditional probability. Hence this will be the required solution for the given question.

Complete step by step answer:
Probability is defined as the extent to which an event is likely to occur. It is measured as a number of favourable events to occur from the total number of events. It is noted that the probability of an event is always \[0 \leqslant P \leqslant 1\], where 0 says the event has not occurred and 1 says the event has occurred. It is equal to the ratio of the number of favourable results and the total number of outcomes. The formula for the probability of an event to occur is given by,
\[P(E) = \dfrac{\text{Number of favourable outcomes}}{\text{Total number of outcomes}}\]

In probability we have two kinds namely, conditional probability and unconditional probability. Now we know about the unconditional probability. An unconditional probability is the probability that a single outcome will result from multiple possible outcomes. The term refers to the likelihood that an event will take place regardless of whether other events have occurred or other conditions exist. In simplest terms, unconditional probability is simply the probability of an event occurring.

Note: Unconditional probability refers to a probability that is unaffected by previous or future events. The unconditional probability of event “A” is denoted as \[P(A)\]. A conditional probability, contrasted to an unconditional probability, is the probability of an event that would be affected by another event.