MACS (for ChIP or ATAC) does not necessarily need a control. There is actually a section in the paper describing exactly the situation where no control is available. In this case, it determines the local lambda in certain windows. The paragraph starts with:
Therefore, instead of using a uniform λBG, estimated from the whole genome, MACS uses a dynamic parameter, λlocal, defined for each candidate peak as (...)
In the absence of a control, naively one would estimate the background level of the experiment in a uniform fashion. That means if you have, say 30mio reads and you randomly threw them onto the genome, then every base (given a certain fragment length of the library) would have a coverage of x. Still, the genome coverage is never uniform (you will most impressively see once you analyze your first WGS sample, it is really a hilly landscape) due to differences in chromatin structure, PCR/GC bias, local copy number alterations etc. So instead of a genome-wide λBG, MACS checks the vicinity of the peak centers (up to 10kb) to estimate how prone this genomic region is to accumulate reads. In my understanding, as a typical ChIPseq experiment produces sharp peaks, the local environment should be depleted for enriched signals. Therefore, notable readcounts in the vicinity are an indication of a local bias. As a result, the peak enrichment needs to be penalized (down-corrected), as the region itself is prone to accumulate enrichment, irrespective of the protein target.